Effective DOA Estimation Under Low Signal-to-Noise Ratio Based on Multi-Source Information Meta Fusion

Efficiently performing high-resolution direction of arrival(DOA)estimation under low signal-to-noise ratio(SNR)conditions has always been a challenge task in the literatures.Obvi-ously,in order to address this problem,the key is how to mine or reveal as much DOA related in-formation as possible from the degraded array outputs.However,it is certain that there is no per-fect solution for low SNR DOA estimation designed in the way of winner-takes-all.Therefore,this paper proposes to explore in depth the complementary DOA related information that exists in spa-tial spectrums acquired by different basic DOA estimators.Specifically,these basic spatial spec-trums are employed as the input of multi-source information fusion model.And the multi-source in-formation fusion model is composed of three heterogeneous meta learning machines,namely neural networks(NN),support vector machine(SVM),and random forests(RF).The final meta-spec-trum can be obtained by performing a final decision-making method.Experimental results illus-trate that the proposed information fusion based DOA estimation method can really make full use of the complementary information in the spatial spectrums obtained by different basic DOA estim-ators.Even under low SNR conditions,promising DOA estimation performance can be achieved.

Influence of signal-to-noise ratio on accuracy of spectral analysis by near infrared spectroscopy

As one of the important indicators of spectrometer,signal-to-noise ratio(SNR)reflects the ability of spectrometer to detect weak signals.To investigate the influence of SNR on the prediction accuracy of spectral analysis,we first introduce the major factors affecting the spectral SNR.Taking green tea as an example,the influence of spectral SNR on the prediction accuracy of the origin identification model is analyzed by experiments.At the same time,the relationship between the spectral SNR and prediction accuracy of spectral analysis model is fitted.Based on this,the common methods for improving the spectral SNR are discussed.The results show that the accuracy of the prediction set model first decreases slowly,then decreases linearly,and finally tends to be flat as the spectral SNR decreases.Through calculation,in order to achieve the prediction accuracy of prediction model reaching 90%and 85%,the spectral SNR is required to be higher than 23.42 dB and 21.16 dB,respectively.The overall results provide certain parameters support for the development of new online analytical spectroscopic instruments,especially for the technical indicators of SNR.

Signal-to-noise ratio comparison of angular signal radiography and phase stepping method

Grating-based x-ray phase contrast imaging has the potential to be applied in future medical applications as it is compatible with both laboratory and synchrotron source. However, information retrieval methods are important because acquisition speed, scanning mode, image quality, and radiation dose depend on them. Phase-stepping （PS） is a widely used method to retrieve information, while angular signal radiography （ASR） is a newly established method. In this manuscript, signal-to-noise ratios （SNRs） of ASR are compared with that of PS. Numerical experiments are performed to validate theoretical results. SNRs comparison shows that for refraction and scattering images ASR has higher SNR than PS method, while for absorption image both methods have same SNR. Therefore, our conclusions would have guideline in future preclinical and clinical applications.

Speech Separation Methodology for Hearing Aid

In the design of hearing aids(HA),the real-time speech-enhancement is done.The digital hearing aids should provide high signal-to-noise ratio,gain improvement and should eliminate feedback.In generic hearing aids the perfor-mance towards different frequencies varies and non uniform.Existing noise can-cellation and speech separation methods drops the voice magnitude under the noise environment.The performance of the HA for frequency response is non uni-form.Existing noise suppression methods reduce the required signal strength also.So,the performance of uniform sub band analysis is poor when hearing aid is con-cern.In this paper,a speech separation method using Non-negative Matrix Fac-torization(NMF)algorithm is proposed for wavelet decomposition.The Proposed non-uniformfilter-bank was validated by parameters like band power,Signal-to-noise ratio(SNR),Mean Square Error(MSE),Signal to Noise and Dis-tortion Ratio(SINAD),Spurious-free dynamic range(SFDR),error and time.The speech recordings before and after separation was evaluated for quality using objective speech quality measures International Telecommunication Union-Telecommunication standard ITU-T P.862.

Consistency in responses to conspecific advertisement calls with various signal-to-noise ratios in both sexes of the Anhui tree frog

Environmental noise has a significant negative impact on acoustic communication in most situations,as it influences the production,transmis-sion,and reception of acoustic signals.However,how animals respond to conspecific sounds when there is interference from environmental noise,and whether males and females display convergent behavioral responses in the face of noise masking remain poorly understood.In this study,we investigated the effects of conspecific male advertisement calls with different signal-to-noise ratios on male-male competition and female choice in the Anhui tree frog Rhacophorus zhoukaiyae using playback and phonotaxis experiments,respectively.The results showed that(1)female Anhui tree frogs preferentially selected the conspecific calls with higher SNR compared to calls with lower SNR;(2)males preferen-tially responded vocally to the conspecific calls with higher SNR compared to calls with lower SNR;and(3)males'competitive strategies were flexible in the face of noise interference.These results suggest that preferences of both sexes converge in outcome,and that male competitive strategies may depend on predictable female preferences.This study will provide an important basis for further research on decision-making in animals.

Long term integration of radar signals with unknown Doppler shift for ubiquitous radar

Ubiquitous radar is a new radar system that provides continuous and uninterrupted multifunction capability within a coverage volume. Continuous coverage from close-in ＂pop-up＂ targets in clutter to long-range targets impacts selection of waveform parameters. The coherent processing interval （CPI） must be long enough to achieve a certain signal-to-noise ratio （SNR） that ensures the efficiency of detection. The condition of detection in the case of low SNR is analyzed, and three different cases that would occur during integration are discussed and a method to determine the CPI is presented. The simulation results show that targets detection with SNR as low as -26 dB in the experimental system can possibly determine the CPI.

Nonsaturation Throughput Enhancement of IEEE 802.11b Distributed Coordination Function for Heterogeneous Traffic under Noisy Environment

In this paper, we propose a mechanism named modified backoff （MB） mechanism to decrease the channel idle time in IEEE 802.11 distributed coordination function （DCF）. In the noisy channel, when signal-to-noise ratio （SNR） is low, applying this mechanism in DCF greatly improves the throughput and lowers the channel idle time. This paper presents an analytical model for the performance study of IEEE 802.11 MB-DCF for nonsaturated heterogeneous traffic in the presence of transmission errors. First, we introduce the MB-DCF and compare its performance to IEEE 802.11 DCF with binary exponential backoff （BEB）. The IEEE 802.11 DCF with BEB mechanism suffers from more channel idle time under low SNR. The MB-DCF ensures high throughput and low packet delay by reducing the channel idle time under the low traffic in the network. However, to the best of the authors＇ knowledge, there are no previous works that enhance the performance of the DCF under imperfect wireless channel. We show through analysis that the proposed mechanism greatly outperforms the original IEEE 802.11 DCF in the imperfect channel condition. The effectiveness of physical and link layer parameters on throughput performance is explored. We also present a throughput investigation of the heterogeneous traffic for different radio conditions.

A BLIND SNR ESTIMATOR FOR DIGITAL BANDPASS SIGNALS

A subspace-based blind Signal-to-Noise Ratio (SNR) estimation algorithm for digital bandpass signals in Additive White Gaussian Noise (AWGN) channel is discussed. The lower bounds of the mean and variance of the estimation are derived, and simulations are performed for the commonly used digital bandpass signals, such as MPSK (M=2, 4, 8), MFSK (M=2, 4) and MQAM (M=16, 64, 128, 256) signals. Theoretical analyses and simulation results indicate that the proposed algorithm is ef- fective even when the SNR is below 0dB. Furthermore, the algorithm can provide a blind estimator in that it needs neither the parameters of the received signals, such as the carrier frequency, symbol rate and modulation scheme, nor the synchronization of the system.

Influence of array elements’ consistency on SNR of hydrophone array

The influence of array element’s consistency on the hydrophone array’s signal-to-noise ratio (SNR) is studied. The consistency of array elements means the outputs of all the array’s elements are the same, that is to say, the outputs have the same phase and amplitude when their inputs are the same. The relationship between the SNR and the correlation coefficient of signal and the relationship between the SNR and the correlation coefficient of noise are given. Hydrophone array’s gain with the output of elements’ inconsistent phase and amplitude is analyzed theoretically. When the signal is single-frequency, the gain expression of two-elements array is deduced. Then the gain is calculated when the phase difference is 10° and the amplitude difference is 3 dB. The theoretical analysis is verified through simulation. The simulation results show the variation rule of array’s SNR when the consistency changes: the array SNR gain is greatly affected by the consistency of the elements’ output and the gain decreases as the consistency decreases and the gain may be negative when the amplitude response becomes worse.

A NOVEL METHOD FOR ESTIMATING THE SNR OF UNKNOWN EMITTER SIGNAL

It is important to estimate the Signal-to-Noise Ratio(SNR) of unknown emitter signal accurately.In order to resolve the disadvantages of present algorithm,a novel method is proposed in this letter.We extract and normalize the information of zero frequency of received signal by the Wigner-Vile Distribution(WVD) transformation and then get the approximate power of original signal by mathematic transformation,at last,we get the estimate value of SNR by the known account formula of SNR.Simulation results show that it is correct and feasible.

Blind parameter estimation of pseudo-random binary code-linear frequency modulation signal based on Duffing oscillator at low SNR

Conventional parameter estimation methods for pseudo-random binary code-linear frequency modulation(PRBC-LFM)signals require prior knowledge,are computationally complex,and exhibit poor performance at low signal-to-noise ratios(SNRs).To overcome these problems,a blind parameter estimation method based on a Duffing oscillator array is proposed.A new relationship formula among the state of the Duffing oscillator,the pseudo-random sequence of the PRBC-LFM signal,and the frequency difference between the PRBC-LFM signal and the periodic driving force signal of the Duffing oscillator is derived,providing the theoretical basis for blind parameter estimation.Methods based on amplitude method,short-time Fourier transform method,and power spectrum entropy method are used to binarize the output of the Duffing oscillator array,and their performance is compared.The pseudo-random sequence is estimated using Duffing oscillator array synchronization,and the carrier frequency parameters are obtained by the relational expressions and characteristics of the difference frequency.Simulation results show that this blind estimation method overcomes limitations in prior knowledge and maintains good parameter estimation performance up to an SNR of-35 dB.

SUBSPACE-BASED NOISE VARIANCE AND SNR ESTIMATION FOR MIMO OFDM SYSTEMS

This paper proposes a subspace-based noise variance and Signal-to-Noise Ratio (SNR) estimation algorithm for Multi-Input Multi-Output (MIMO) wireless Orthogonal Frequency Division Multiplexing (OFDM) systems. The special training sequences with the property of orthogonality and phase shift orthogonality are used in pilot tones to obtain the estimated channel correlation matrix. Partitioning the observation space into a delay subspace and a noise subspace, we achieve the measurement of noise variance and SNR. Simulation results show that the proposed estimator can obtain accurate and real-time measurements of the noise variance and SNR for various multipath fading channels, demonstrating its strong robustness against different channels.

Effect of Peak Power and Pulse Width on Coherent Doppler Wind Lidar’s SNR

The laser device is the core component of coherent Doppler wind lidar.The peak power and pulse width of laser transmitting pulse have important effects on SNR.Based on coherent Doppler wind pulse lidar,the peak power and pulse width influence on SNR is studied on the theoretical derivation and analysis,and the results show that the higher the peak power can realize the greater the signal-to-noise ratio of coherent Doppler wind lidar.But when the peak power is too large,the laser pulse may appear nonlinear phenomenon,which cause the damage of the laser.So,the peak power must be less than the stimulated brillouin scattering power threshold.Increasing the pulse width can make the laser device to output more energy,but it will also make the spatial resolution lower,and the influence of turbulence on SNR will be greater.After a series of simulation analyses,it can be concluded that when the peak power is 650W and the pulse width is 340ns,the SNR of the system can be maximized.In addition,the coherent Doppler wind lidar system is set up to carry out corresponding experimental verification.The experimental results are consistent with the theoretical analysis and simulation,which verifies the correctness of the theoretical analysis and simulation results.It provides theoretical basis and practical ex-perience for the design of laser transmitting pulse in coherent Doppler wind lidar system.

Parametric SNR Estimation Based on Auto-Regressive Model in AWGN Channels

Signal-to-noise ratio（SNR）estimation for signal which can be modeled by Auto-regressive（AR）process is studied in this paper.First,the conventional frequency domain method is introduced to estimate the SNR for the received signal in additive white Gauss noise（AWGN）channel.Then a parametric SNR estimation algorithm is proposed by taking advantage of the AR model information of the received signal.The simulation results show that the proposed parametric method has better performance than the conventional frequency doma in method in case of AWGN channel.

Carrier Synchronization for Very Low SNR

The Turbo decoding performance will suffer serious degradation under low signal-to-noise ratios （SNR） conditions for the reason of residual frequency and phase offset in the carrier. In this paper, an improved residual carrier frequency offset estimation algorithm based on a priori probability aided （APPA） phase estimation is proposed. A carrier synchronization loop that combines the iterative turbo decoder and the phase estimator together is constructed, where the extrinsic information obtained from the Turbo decoder is used to aid an iterative phase estimation process. The simulation results show that the algorithm performs successfully under very low SNR conditions （for example, less than -7.4 dB） with large frequency offset and phase error and the performance of this algorithm is very close to the optimally synchronized system.

Target tracking methods based on a signal-to-noise ratio model

In traditional target tracking methods,the angle error and range error are often measured by the empirical value,while observation noise is a constant.In this paper,the angle error and range error are analyzed.They are influenced by the signalto-noise ratio(SNR).Therefore,a model related to SNR has been established,in which the SNR information is applied for target tracking.Combined with an advanced nonlinear filter method,the extended Kalman filter method based on the SNR model(SNR-EKF)and the unscented Kalman filter method based on the SNR model(SNR-UKF)are proposed.There is little difference between the SNR-EKF and SNR-UKF methods in position precision,but the SNR-EKF method has advantages in computation time and the SNR-UKF method has advantages in velocity precision.Simulation results show that target tracking methods based on the SNR model can greatly improve the tracking performance compared with traditional tracking methods.The target tracking accuracy and convergence speed of the proposed methods have significant improvements.

Optimizing Optical Attocells Positioning of Indoor Visible Light Communication System

Visible light communication(VLC),which is a prominent emerging solution that complements the radio frequency(RF)technology,exhibits the potential to meet the demands of fifth-generation(5G)and beyond technologies.The random movement of mobile terminals in the indoor environment is a challenge in the VLC system.The model of optical attocells has a critical role in the uniform distribution and the quality of communication links in terms of received power and signal-to-noise ratio(SNR).As such,the optical attocells positions were optimized in this study with a developed try and error(TE)algorithm.The optimized optical attocells were examined and compared with previous models.This novel approach had successfully increased minimum received power from−1.29 to−0.225 dBm,along with enhanced SNR performance by 2.06 dB.The bit error rate(BER)was reduced to 4.42×10−8 and 6.63×10−14 by utilizing OOK-NRZ and BPSK modulation techniques,respectively.The optimized attocells positions displayed better uniform distribution,as both received power and SNR performances improved by 0.45 and 0.026,respectively.As the results of the proposed model are optimal,it is suitable for standard office and room model applications.

Slab Yb：YAG pulse amplifier with high amplification gain and signal-to-noise ratio

This study experimentally investigated a Yb： YAG pulse laser amplifier with a high amplification gain and a high signal-to-noise ratio （SNR）. The highest amplification gain of 172 and highest pulse energy of 131 mJ were obtained with the highest SNR of 24.9 dB from a volume gain of 10 mm × 10 mm × 1 mm. The output beam quality values ofM2 = 1.91 in the slow axis and M2 = 1.58 in the fast axis were also achieved.

Simple and effective method to improve the signal-to-noise ratio of compressive imaging

This Letter presents a simple and effective method to improve the signal-to-noise ratio（SNR） of compressing imaging. The main principles of the proposed method are the correlation of the image signals and the randomness of the noise. Multiple low SNR images are reconstructed firstly by the compressed sensing reconstruction algorithm, and then two-dimensional time delay integration technology is adopted to improve the SNR. Results show that the proposed method can improve the SNR performance efficiently and it is easy to apply the a lgorithm to the real project.

噪声对离散混沌系统非线性特征量的影响

以Logistic映像为例,运用非线性动力学的方法,分析了不同信噪比时,噪声对离散映像在混沌区非线性特征量的影响.通过错误近邻分析法确定序列的嵌入维,计算了序列的关联维数、最大Lyapunov指数和近似熵,结果表明:随着信噪比的降低,关联维数和近似熵逐渐增大,最大Lyapunov指数呈下降趋势;当信噪比大于500时,噪声对非线性特征量的影响不大.并采用重现图形和重现定量分析法得出信噪比大于10时序列存在的确定性规律仍能显示出来.